Given　decoupling　the　control　layer　and　the　infrastructure　layer,　the　software-defined　wireless　networks　(SDWNs)　is　beneficial　in　terms　of　providing　both　low-latency　and　low-energy　consumption　services　for　mobile　users,　where　multicontroller　placement　and　resource　management　become　a　pair　of　bottlenecks.　In　this　letter,　we　propose　an　energy-aware　multicontroller　placement　scheme　as　well　as　a　latency-aware　resource　management　model　for　the　SDWN.　Moreover,　the　particle　swarm　optimization　is　invoked　for　solving　the　multi-controller　placement　problem,　and　a　deep　reinforcement　learning　algorithm-aided　resource　allocation　strategy　is　conceived.　Finally,　experimental　results　show　that　our　proposed　schemes　are　conducive　to　reducing　both　the　execution　time　and　the　energy　consumption　of　each　task.